README.md

metadata

library_name: transformers
license: apache-2.0
base_model: google/bert_uncased_L-4_H-512_A-8
tags:
  - generated_from_trainer
datasets:
  - gokulsrinivasagan/processed_wikitext-103-raw-v1-ld
metrics:
  - accuracy
model-index:
  - name: tinybert_base_train_book_ent_15p_s_init
    results:
      - task:
          name: Masked Language Modeling
          type: fill-mask
        dataset:
          name: gokulsrinivasagan/processed_wikitext-103-raw-v1-ld
          type: gokulsrinivasagan/processed_wikitext-103-raw-v1-ld
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.1853157281132229

tinybert_base_train_book_ent_15p_s_init

This model is a fine-tuned version of google/bert_uncased_L-4_H-512_A-8 on the gokulsrinivasagan/processed_wikitext-103-raw-v1-ld dataset. It achieves the following results on the evaluation set:

• Loss: 5.6359
• Accuracy: 0.1853

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 0.0001
• train_batch_size: 200
• eval_batch_size: 200
• seed: 10
• optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 10000
• num_epochs: 24

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
5.3929	8.7413	10000	5.9672	0.1618
5.8297	17.4825	20000	5.6359	0.1853

Framework versions

• Transformers 4.51.2
• Pytorch 2.6.0+cu126
• Datasets 3.5.0
• Tokenizers 0.21.1